Introduction to Data Science and Machine Learning
The course will give an introduction to the emerging field of Data Science with special focus on machine learning. The course combines lectures with hands-on exercises and is designed to give an overview over the diverse aspects of the daily work of a Data Scientist from a practical perspective.
Students will learn how to evaluate a use-case regarding the application of machine learning methods, how to explore data and build a machine learning model. Students will learn how to assess the quality of a prediction made by a machine learning model and get an overview about key statistical concept relevant for Data Scientists.
At the end of the course students will be able to:
- Understand the fundamental principles of machine learning
- Evaluate use-cases w.r.t. application of machine learning techniques
- Understand data exploration techniques to get an understanding of the data
- Build a simple machine learning model
- Evaluate the quality of the predictions of the machine learning model
- Understand key statistical concepts relevant for the work of a Data Scientist
- Due to the interactive teaching format, the number of participants is limited to 20. Advanced master students are invited to participate. However, they should be in the second half of their respective MSc program.
- All hands-on sessions will be done using python with modules relevant for Data Science, prior exposure to programming, esp. in python is helpful.
The final grade will based on the quality of contributions to discussions and hands-on exercises (50%), as well as the written assignment (50%).